Para ver las publicaciones de todo Robótica y Manufactura Avanzada, ver: Publicaciones RYMA
2016
Artículos de revista
Perez-Alcocer, R. R.; Torres-Mendez, Luz Abril; Olguin-Diaz, Ernesto; Maldonado-Ramirez, Alejandro
Vision-based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions using a Model-free Robust Control Artículo de revista
En: 2016.
@article{P\'{e}rez-Alcocer2016,
title = {Vision-based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions using a Model-free Robust Control},
author = {Perez-Alcocer, R. R. and Torres-Mendez, Luz Abril and Olguin-Diaz, Ernesto and Maldonado-Ramirez, Alejandro },
year = {2016},
date = {2016-06-06},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril
Robotic Visual Tracking of Relevant Cues in Underwater Environments with Poor Visibility Conditions Artículo de revista
En: Journal of Sensors, vol. 2016, 2016.
@article{maldonado2016robotic,
title = {Robotic Visual Tracking of Relevant Cues in Underwater Environments with Poor Visibility Conditions},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril},
url = {https://www.hindawi.com/journals/js/2016/4265042/},
year = {2016},
date = {2016-01-01},
journal = {Journal of Sensors},
volume = {2016},
publisher = {Hindawi Publishing Corporation},
abstract = {Using visual sensors for detecting regions of interest in underwater environments is fundamental for many robotic applications. Particularly, for an autonomous exploration task, an underwater vehicle must be guided towards features that are of interest. If the relevant features can be seen from the distance, then smooth control movements of the vehicle are feasible in order to position itself close enough with the final goal of gathering visual quality images. However, it is a challenging task for a robotic system to achieve stable tracking of the same regions since marine environments are unstructured and highly dynamic and usually have poor visibility. In this paper, a framework that robustly detects and tracks regions of interest in real time is presented. We use the chromatic channels of a perceptual uniform color space to detect relevant regions and adapt a visual attention scheme to underwater scenes. For the tracking, we associate with each relevant point superpixel descriptors which are invariant to changes in illumination and shape. The field experiment results have demonstrated that our approach is robust when tested on different visibility conditions and depths in underwater explorations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Using visual sensors for detecting regions of interest in underwater environments is fundamental for many robotic applications. Particularly, for an autonomous exploration task, an underwater vehicle must be guided towards features that are of interest. If the relevant features can be seen from the distance, then smooth control movements of the vehicle are feasible in order to position itself close enough with the final goal of gathering visual quality images. However, it is a challenging task for a robotic system to achieve stable tracking of the same regions since marine environments are unstructured and highly dynamic and usually have poor visibility. In this paper, a framework that robustly detects and tracks regions of interest in real time is presented. We use the chromatic channels of a perceptual uniform color space to detect relevant regions and adapt a visual attention scheme to underwater scenes. For the tracking, we associate with each relevant point superpixel descriptors which are invariant to changes in illumination and shape. The field experiment results have demonstrated that our approach is robust when tested on different visibility conditions and depths in underwater explorations.
Conferencias
Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril
A Bag of Relevant Regions Model for Place Recognition in Coral Reefs Conferencia
OCEANS 2016, IEEE 2016.
@conference{maldonado2016bag,
title = {A Bag of Relevant Regions Model for Place Recognition in Coral Reefs},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril },
year = {2016},
date = {2016-01-01},
booktitle = {OCEANS 2016},
pages = {1--5},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
2015
Artículos de revista
Castelan, Mario; Cruz-Perez, Elier; Torres-Mendez, Luz Abril
A Photometric Sampling Strategy for Reflectance Characterization and Transference Artículo de revista
En: Computación y Sistemas, vol. 19, no 2, pp. 255-272, 2015.
@article{Castelan2015,
title = {A Photometric Sampling Strategy for Reflectance Characterization and Transference},
author = {Castelan, Mario and Cruz-Perez, Elier and Torres-Mendez, Luz Abril},
url = {http://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/1944},
year = {2015},
date = {2015-01-01},
journal = {Computaci\'{o}n y Sistemas},
volume = {19},
number = {2},
pages = {255-272},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2014
Artículos de revista
Martinez-Garcia, Edgar A.; Torres-Mendez, Luz Abril; Elara Mohan, Rajesh
Multi-legged robot dynamics navigation model with optical flow Artículo de revista
En: International Journal of Intelligent Unmanned Systems, vol. 2, no 2, pp. 121-139, 2014.
@article{doi:10.1108/IJIUS-04-2014-0003,
title = {Multi-legged robot dynamics navigation model with optical flow},
author = {Martinez-Garcia, Edgar A. and Torres-Mendez, Luz Abril and Elara Mohan, Rajesh },
url = {http://dx.doi.org/10.1108/IJIUS-04-2014-0003},
doi = {10.1108/IJIUS-04-2014-0003},
year = {2014},
date = {2014-01-01},
journal = {International Journal of Intelligent Unmanned Systems},
volume = {2},
number = {2},
pages = {121-139},
abstract = {Purpose \textendash The purpose of this paper is to establish analytical and numerical solutions of a navigational law to estimate displacements of hyper-static multi-legged mobile robots, which combines: monocular vision (optical flow of regional invariants) and legs dynamics. Design/methodology/approach \textendash In this study the authors propose a Euler-Lagrange equation that control legs’ joints to control robot's displacements. Robot's rotation and translational velocities are feedback by motion features of visual invariant descriptors. A general analytical solution of a derivative navigation law is proposed for hyper-static robots. The feedback is formulated with the local speed rate obtained from optical flow of visual regional invariants. The proposed formulation includes a data association algorithm aimed to correlate visual invariant descriptors detected in sequential images through monocular vision. The navigation law is constrained by a set of three kinematic equilibrium conditions for navigational scenarios: constant acceleration, constant velocity, and instantaneous acceleration. Findings \textendash The proposed data association method concerns local motions of multiple invariants (enhanced MSER) by minimizing the norm of multidimensional optical flow feature vectors. Kinematic measurements are used as observable arguments in the general dynamic control equation; while the legs joints dynamics model is used to formulate the controllable arguments. Originality/value \textendash The given analysis does not combine sensor data of any kind, but only monocular passive vision. The approach automatically detects environmental invariant descriptors with an enhanced version of the MSER method. Only optical flow vectors and robot's multi-leg dynamics are used to formulate descriptive rotational and translational motions for self-positioning.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose – The purpose of this paper is to establish analytical and numerical solutions of a navigational law to estimate displacements of hyper-static multi-legged mobile robots, which combines: monocular vision (optical flow of regional invariants) and legs dynamics. Design/methodology/approach – In this study the authors propose a Euler-Lagrange equation that control legs’ joints to control robot's displacements. Robot's rotation and translational velocities are feedback by motion features of visual invariant descriptors. A general analytical solution of a derivative navigation law is proposed for hyper-static robots. The feedback is formulated with the local speed rate obtained from optical flow of visual regional invariants. The proposed formulation includes a data association algorithm aimed to correlate visual invariant descriptors detected in sequential images through monocular vision. The navigation law is constrained by a set of three kinematic equilibrium conditions for navigational scenarios: constant acceleration, constant velocity, and instantaneous acceleration. Findings – The proposed data association method concerns local motions of multiple invariants (enhanced MSER) by minimizing the norm of multidimensional optical flow feature vectors. Kinematic measurements are used as observable arguments in the general dynamic control equation; while the legs joints dynamics model is used to formulate the controllable arguments. Originality/value – The given analysis does not combine sensor data of any kind, but only monocular passive vision. The approach automatically detects environmental invariant descriptors with an enhanced version of the MSER method. Only optical flow vectors and robot's multi-leg dynamics are used to formulate descriptive rotational and translational motions for self-positioning.
Conferencias
Rodriguez-Telles, Francisco G; Perez-Alcocer, Ricardo; Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril; Bikram Dey, Bir; Martinez-Garcia, Edgar A.
Vision-based reactive autonomous navigation with obstacle avoidance: Towards a non-invasive and cautious exploration of marine habitat Conferencia
2014 IEEE International Conference on Robotics and Automation (ICRA), IEEE 2014.
@conference{rodriguez2014vision,
title = {Vision-based reactive autonomous navigation with obstacle avoidance: Towards a non-invasive and cautious exploration of marine habitat},
author = {Rodriguez-Telles, Francisco G and Perez-Alcocer, Ricardo and Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril and Bikram Dey, Bir and Martinez-Garcia, Edgar A.},
year = {2014},
date = {2014-01-01},
booktitle = {2014 IEEE International Conference on Robotics and Automation (ICRA)},
pages = {3813--3818},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril; Martinez-Garcia, Edgar A.
Robust detection and tracking of regions of interest for autonomous underwater robotic exploration Conferencia
Proc. 6th Int. Conf. on Advanced Cognitive Technologies and Applications, 2014.
@conference{maldonado2014robust,
title = {Robust detection and tracking of regions of interest for autonomous underwater robotic exploration},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril and Martinez-Garcia, Edgar A.},
year = {2014},
date = {2014-01-01},
booktitle = {Proc. 6th Int. Conf. on Advanced Cognitive Technologies and Applications},
pages = {165--171},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}